This document relates generally to cardiac rhythm management systems and particularly, but not by way of limitation, to a system providing prediction of a future arrhythmia and preventive therapy for avoiding or mitigating the predicted arrhythmia.
The human heart normally maintains its own well-ordered intrinsic rhythm through generation of stimuli by pacemaker tissue that results in a wave of depolarization that spreads through specialized conducting tissue and then into and through the myocardium. The well-ordered propagation of electrical depolarizations through the heart causes coordinated contractions of the myocardium that results in the efficient pumping of blood. In a normally functioning heart, stimuli are generated under the influence of various physiological regulatory mechanisms to cause the heart to beat at a rate that maintains cardiac output at a level sufficient to meet the metabolic needs of the body. Abnormalities of excitable cardiac tissue, however, can lead to abnormalities of heart rhythm that are called arrhythmias. All arrhythmias stem from one of two causes: abnormalities of impulse generation or abnormalities of impulse propagation. Arrhythmias can cause the heart to beat too slowly (bradycardia, or a bradyarrhythmia) or too quickly (tachycardia, or a tachyarrhythmia), either of which may cause hemodynamic compromise or death.
Drug therapy is often effective in preventing the development of arrhythmias and in restoring normal heart rhythms once an arrhythmia has occurred. However, drug therapy is not always effective for treating particular arrhythmias, and drug therapy usually causes side-effects that may be intolerable in certain patients. For such patients, an alternative mode of treatment is needed. One such alternative mode of treatment includes the use of a cardiac rhythm management system incorporated into an implantable device that delivers therapy to the heart in the form of electrical stimuli. Such implantable devices include cardiac pacemakers that deliver timed sequences of low energy electrical stimuli, called pacing pulses, to the heart, via an intravascular leadwire or catheter (referred to as a lead) having one or more electrodes disposed in or about the heart. Heart contractions are initiated in response to such pacing pulses (referred to as capturing the heart). By properly timing the delivery of pacing pulses, the heart can be induced to contract in proper rhythm, greatly improving its efficiency as a pump. Pacemakers are often used to treat patients with bradycardia. Pacemakers are also capable of delivering paces to the heart in such a manner that the heart rate is slowed, a pacing mode referred to as anti-tachyarrhythmia pacing.
Cardiac rhythm management systems also include cardioverter/defibrillators (ICD""s) that are capable of delivering higher energy electrical stimuli to the heart. ICD""s are often used to treat patients with tachyarrhythmias, that is, hearts that beat too quickly. Tachyarrhythmias can cause diminished blood circulation because the cardiac cycle of systole (contraction) and diastole (filling) can be shortened to such an extent that insufficient blood fills the ventricles during diastole. Besides the potential for such hemodynamic embarrassment, tachyarrhythmias can also degrade into even more serious arrhythmias such as fibrillation where electrical activity spreads through the myocardium in a disorganized fashion so that effective contraction does not occur. For example, in a particular type of tachyarrhythmia, referred to as ventricular fibrillation, the heart pumps little or no blood to the body so that death occurs within minutes. A defibrillator delivers a high energy electrical stimulus or shock to the heart to depolarize all of the myocardium and render it refractory in order to terminate arrhythmia, allowing the heart to reestablish a normal rhythm for the efficient pumping of blood. In addition to ICD""s and pacemakers, cardiac rhythm management systems also include pacemaker/ICD""s that combine the functions of pacemakers and ICD""s, drug delivery devices, and any other implantable or external systems or devices for diagnosing, monitoring, or treating cardiac arrhythmias.
Cardiac rhythm management systems incorporated into ICD""s allow tachyarrhythmias to be automatically detected and treated in a matter of seconds. Defibrillators are usually effective at treating tachyarrhythmias and preventing death, but such devices are not 100% effective at treating all tachyarrhythmias in all patients. As a result, some patients may still die even if the defibrillator delivers appropriate therapy. Also, some patients have frequent tachyarrhythmias, triggering frequent therapeutic shocks. This reduces the usable life of the implanted battery-powered device and increases the risk of therapy-induced complications. Furthermore, even if the device successfully treats the tachyarrhythmia, the patient may lose consciousness during the arrhythmia which can result in related serious or even fatal injuries (e.g., falling, drowning while bathing, car accident while driving, etc.). Thus, there is a need for a cardiac rhythm management system that predicts when an arrhythmia will occur and invokes a therapy to prevent or reduce the consequences of the arrhythmia.
The present invention relates to a system and method for predicting cardiac arrhythmias. In a particular embodiment, the system and method are implemented in an implantable cardiac device having one or more sensing channels for detecting conditioning events (e.g., marker/trigger events as defined below) and the capability of delivering some type of preventive arrhythmia therapy when conditions warrant it.
In accordance with the invention, an arrhythmia is predicted by: 1) detecting a conditioning event statistically associated with the occurrence of an arrhythmia in a patient""s heart; 2) computing a conditional arrhythmia probability for the conditioning event from past observations of instances in which the conditioning event occurs alone or together with an arrhythmia within a specified time period; 3) computing an estimated arrhythmia probability based upon the detected occurrence of the conditioning event; and 4) predicting the occurrence of an arrhythmia within a specified prediction time period if the estimated arrhythmia probability exceeds a specified threshold value.
Conditioning events may be broadly classified into markers and triggers. A marker event corresponds to detected a physiological state that is statistically associated with occurrence of cardiac arrhythmias, but the causal relationship between the marker and the arrhythmia is not known. A conditioning event is regarded as a trigger, on the other hand, if the event is thought to increase the risk of an arrhythmia occurring via a depolarization that serves as a source for the arrhythmia. Conditioning events may be detected on a beat-to-beat basis or over a longer time frame. Examples of conditioning events include a detected specific morphology of a waveform representing the electrical activity of the heart, a specific pattern of activation times of different areas of the heart as sensed by a plurality of electrodes, a specific sequence pattern of heartbeats with respect to time, a value of a measured physiological variable such as heart rate or blood pressure, or a statistic based upon a history of occurrences of conditioning events.
In one embodiment, the conditional arrhythmia probability is calculated as a ratio of the number of observed instances in which the conditioning event is followed by an arrhythmia within a specified basic time period, to the total number of observed instances of the conditioning event. In that case, the estimated arrhythmia probability for an arrhythmia to occur within the specified basic time period after detection of the conditioning event is simply the calculated conditional arrhythmia probability.
In another embodiment, the conditional arrhythmia probability CP is calculated by the expression:
CP=1xe2x88x92exe2x88x92RT
which assumes a Poisson probability distribution, where T is a measure of the specified prediction time period, and R is an estimate of the rate at which arrhythmias occur while the conditioning event is present. The rate R is a ratio of: 1) the number of instances in which the conditioning event is followed by an arrhythmia within a specified basic time period, to 2) the length of the basic time period multiplied by the total number of basic time periods in which the conditioning event is observed. The estimated arrhythmia probability for an arrhythmia to occur within the time T after detection of the conditioning event is again the conditional arrhythmia probability. Calculating the conditional arrhythmia probability in this manner allows the prediction time period T to differ from the length of the basic time period used to derive the conditional arrhythmia probability.
In another embodiment, rather than basing the estimated arrhythmia probability upon the detection of a conditioning event, a rate at which the conditioning event occurs is detected over some period of time. The estimated arrhythmia probability is then calculated as the product of an estimated probability that a conditioning event will occur times the probability of an arrhythmia occurring within specified time period given the occurrence of the conditioning event (i.e. the conditional arrhythmia probability). Thus:
estimated arrhythmia probability=(1xe2x88x92exe2x88x92RT)(1xe2x88x92exe2x88x92CT)
where T is a measure of the specified prediction time period, R is an estimate of the rate at which arrhythmias occur while the conditioning event is present, and C is an estimate of the rate at which the conditioning event occurs.
Another way of deriving a conditional arrhythmia probability, especially for trigger-types of conditioning events (although it can be used with any type of conditioning event), is to designate a particular detected trigger event as being responsible for causing a detected arrhythmia. Such culpability may be assigned based, e.g., upon the proximity in time between the trigger event and the onset of the arrhythmia, the magnitude of the detected trigger, or the frequency of occurrence of the trigger event within a specific time period prior to the onset of the arrhythmia. A conditional arrhythmia probability CP for that trigger event can then be calculated as a ratio of the number of instances in which the trigger event was deemed culpable for causing an arrhythmia, to the total number of occurrences of the trigger event. Also, as above, rather than basing the estimated arrhythmia probability upon the detection of the trigger event, a rate at which the trigger event occurs can be detected over some period of time. The estimated arrhythmia probability is then calculated as the product of an estimated probability that a trigger event will occur times the probability CP of an arrhythmia occurring within a specified time period T given the occurrence of the trigger event. Thus:
estimated arrhythmia probability=CPxc3x97(1xe2x88x92exe2x88x92CT)
In a preferred embodiment, the prediction of arrhythmias is based upon a plurality of the same or different detected conditioning events. A composite estimated arrhythmia probability is then computed as a combination of the estimated arrhythmia probabilities derived for each separately detected conditioning event. The separately detected conditioning events may be separate occurrences of the same or different conditioning events. As before, the composite arrhythmia probability is compared with a threshold value in order to predict the occurrence of an arrhythmia. In one embodiment, the composite arrhythmia probability is calculated by adding the individual estimated arrhythmia probabilities derived for each detected conditioning event, which thus assumes each individual arrhythmia probability to correspond to an independent event. In other embodiments, specific combinations of detected conditioning events are mapped in a non-linear fashion to estimated arrhythmia probabilities that can be added or otherwise combined with other estimated arrhythmia probabilities to give a composite value. In still other embodiments, the estimated arrhythmia probability is computed from a combination of conditional arrhythmia probabilities derived using different basic time periods but for the same prediction time period.
The past observations of the occurrences of conditioning events and arrhythmias from which the conditional arrhythmia probabilities are derived can be taken from either population data or from data collected in real-time from a particular patient. In a preferred embodiment, the conditional arrhythmia probabilities are based initially upon past observations of the occurrences of events and arrhythmias taken from population data, and each probability is subsequently updated from a previous value to a present value with observations taken in real-time from a particular patient. In one embodiment, a conditional arrhythmia probability is updated only if the present value differs by a predetermined amount from the previous value. In another embodiment, the amount by which the present value differs from the previous value is tested for statistical significance before a conditional arrhythmia probability is updated. In another embodiment, the previous value of the conditional arrhythmia probability is incremented or decremented by a specific amount after a prediction time period in accordance with whether the arrhythmia occurred or not, respectively.
In still another embodiment, the statistical association between the conditioning event and the occurrence of an arrhythmia is periodically reevaluated using the most recent patient-specific data. If the statistical association (e.g., as a calculated from a chi-square test) is found to be below a specified value, the use of that conditional arrhythmia probability in deriving a composite estimated arrhythmia probability is discontinued.
As aforesaid, one embodiment of the invention involves delivering preventive arrhythmia therapy if the estimated probability of an arrhythmia occurring within a specified time period (i.e., the composite estimated arrhythmia probability) exceeds a threshold value so that an arrhythmia can be predicted with some degree of certainty. Examples of such therapies capable of being delivered by an implantable device include the delivery of pharmacologic agents, pacing the heart in a particular mode, delivery of cardioversion/defibrillation shocks to the heart, or neural stimulation (e.g., stimulation of either the sympathetic or parasympathetic branches of the autonomic nervous system). Another type of therapy capable of being delivered by an implantable device in accordance with the invention (interpreting the term xe2x80x9ctherapyxe2x80x9d in a broad sense) is issuance of a warning signal that an arrhythmia has been predicted, which warning signal may take the form of a audible signal, a radio-transmitted signal, or any other type of signal that would alert the patient or physician to the possibility of an impending arrhythmia. Such a warning signal would allow the patient to take precautionary measures and/or allow a treating physician to take other therapeutic steps if deemed appropriate. In accordance with the invention, the selection of a particular therapy to be delivered or not is based upon ascertaining a physiologic state of the patient and deciding whether or not a particular available modality of therapy is appropriate for delivery to the patient in that physiologic state.
The modality selection process in one embodiment takes the form of a matrix mapping of a state vector representing a specific physiologic state (as determined by, e.g., the particular conditioning events used to make the arrhythmia prediction, the prediction time period for the estimated arrhythmia probability, the presence or not of specific conditioning events within a specified prior time period, or the magnitude and/or presence other detected and/or calculated variables) to a specific therapy or therapies considered most appropriate for preventing an arrhythmia in that instance (i.e., a point in xe2x80x9ctherapy spacexe2x80x9d). The matrix mapping is performed using a therapy matrix containing information relating to whether or not (and/or to what extent) a particular therapy modality is expected to be effective for a given physiologic state. The elements of the therapy matrix may thus constitute variables representing the appropriateness of a particular therapy modality given the presence of a specific element in the physiological state vector.
In one particular embodiment, a prediction scheduler makes separate predictions for each time period in which an arrhythmia may or may not be predicted to occur (i.e., the prediction time period) and then makes a therapy decision using a therapy matrix specific for that prediction time period. In this manner, a therapy decision for a given therapy modality may be made with respect to the time period appropriate for that modality. For example, some therapy modalities can be expected to be effective in a short time period and are thus suitable for preventing an arrhythmia with a short prediction time period, while others would not be expected to be effective until after a longer time interval and therefore would only be suitable if the prediction time period were commensurate. In another embodiment, therapy decisions and predictions are made at time intervals without regard to the arrhythmia prediction periods, and the therapy matrix takes into account the prediction time period for the estimated arrhythmia probability. For example, the prediction time period may be incorporated into the physiologic state vector, and the therapy matrix then contains information related to the appropriateness of each available therapy modality for a given prediction time period.
Rather than estimating a probability for the occurrence of any arrhythmia, separate estimated arrhythmia probabilities can be computed for different types of arrhythmias in accordance with the invention. By computing such separate probabilities, a more informed decision as to what mode of therapeutic intervention to employ may be made. The most beneficial set of separate estimated arrhythmia probabilities for any particular patient be expected to vary. Accordingly, selection of the arrhythmia types for which separate estimated arrhythmia probabilities are computed can be done dynamically by tabulating the number of detected occurrences of each specific type of arrhythmia and computing separate estimated arrhythmia probabilities for those arrhythmia types occurring most frequently in the patient. Separate estimated arrhythmia probabilities can also be computed for different types of trigger events. Such trigger events can be expected to be patient-specific, and the particular mix of trigger events for which separate arrhythmia probabilities are calculated can be selected dynamically as described above.